public class Imputer extends Estimator<ImputerModel> implements ImputerParams, DefaultParamsWritable
Note when an input column is integer, the imputed value is casted (truncated) to an integer type. For example, if the input column is IntegerType (1, 2, 4, null), the output will be IntegerType (1, 2, 4, 2) after mean imputation.
Note that the mean/median value is computed after filtering out missing values. All Null values in the input columns are treated as missing, and so are also imputed. For computing median, DataFrameStatFunctions.approxQuantile is used with a relative error of 0.001.
Modifier and Type | Method and Description |
---|---|
Imputer |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
ImputerModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
Param<String> |
inputCol()
Param for input column name.
|
StringArrayParam |
inputCols()
Param for input column names.
|
static Imputer |
load(String path) |
DoubleParam |
missingValue()
The placeholder for the missing values.
|
Param<String> |
outputCol()
Param for output column name.
|
StringArrayParam |
outputCols()
Param for output column names.
|
static MLReader<T> |
read() |
DoubleParam |
relativeError()
Param for the relative target precision for the approximate quantile algorithm.
|
Imputer |
setInputCol(String value) |
Imputer |
setInputCols(String[] value) |
Imputer |
setMissingValue(double value) |
Imputer |
setOutputCol(String value) |
Imputer |
setOutputCols(String[] value) |
Imputer |
setRelativeError(double value) |
Imputer |
setStrategy(String value)
Imputation strategy.
|
Param<String> |
strategy()
The imputation strategy.
|
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
params
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getInOutCols, getMissingValue, getStrategy, validateAndTransformSchema
getInputCol
getInputCols
getOutputCol
getOutputCols
getRelativeError
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
toString
write
save
$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize
public static Imputer load(String path)
public static MLReader<T> read()
public final Param<String> strategy()
ImputerParams
strategy
in interface ImputerParams
public final DoubleParam missingValue()
ImputerParams
missingValue
in interface ImputerParams
public final DoubleParam relativeError()
HasRelativeError
relativeError
in interface HasRelativeError
public final StringArrayParam outputCols()
HasOutputCols
outputCols
in interface HasOutputCols
public final Param<String> outputCol()
HasOutputCol
outputCol
in interface HasOutputCol
public final StringArrayParam inputCols()
HasInputCols
inputCols
in interface HasInputCols
public final Param<String> inputCol()
HasInputCol
inputCol
in interface HasInputCol
public String uid()
Identifiable
uid
in interface Identifiable
public Imputer setInputCol(String value)
public Imputer setOutputCol(String value)
public Imputer setInputCols(String[] value)
public Imputer setOutputCols(String[] value)
public Imputer setStrategy(String value)
value
- (undocumented)public Imputer setMissingValue(double value)
public Imputer setRelativeError(double value)
public ImputerModel fit(Dataset<?> dataset)
Estimator
fit
in class Estimator<ImputerModel>
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
We check validity for interactions between parameters during transformSchema
and
raise an exception if any parameter value is invalid. Parameter value checks which
do not depend on other parameters are handled by Param.validate()
.
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema
in class PipelineStage
schema
- (undocumented)public Imputer copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Estimator<ImputerModel>
extra
- (undocumented)